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1.
电离层总电子含量(TEC)不仅是分析电离层形态的关键参数之一,同时为导航及定位等空间应用系统消除电离层附加时延提供重要支撑。由于电离层TEC的时空变化特征,本文融合因果卷积和长短时记忆网络,以太阳活动指数F10.7、地磁活动指数Dst和电离层TEC历史数据作为特征输入,构建深度学习模型,实现提前24 h预报电离层TEC。进一步利用2005-2013年连续9年的CODE TEC数据,全面评估了模型在北京站(40°N,115°E)、武汉站(30.53°N,114.36°E)和海口站(20.02°N,110.38°E)的预报性能。结果显示不同太阳活动条件下三个站的TEC值与真实测量值的相关系数都大于0.87,均方根误差大都集中在0~1 TECU以内,且模型预报精度与纬度、太阳、地磁活动程度、季节变化相关。与仅由长短时记忆网络构成的预报模型相比,本实验模型均方根误差降低了15%,为电离层TEC预报模型的实际应用提供了参考。   相似文献   

2.
一种电离层TEC格点预测模型   总被引:1,自引:1,他引:0  
基于分析时间序列数据的门限控制单元(GRU)神经网络模型,利用电离层TEC网格点历史数据、太阳活动指数、地磁活动指数作为预测因子,提出一种高精度电离层TEC格点预测模型.对全球60个网格点的数据进行了模型预测和对比实验,得到北半球平均相对精度的均值为83.96%,高于南半球的73.60%,表明预测模型在北半球的适应性更好,且中低纬地区的适应性优于高纬地区;预测模型在磁扰动期的平均相对精度的均值比磁平静期平均相对精度的均值高,约1.95%;与基于递归神经网络(RNN)、长短时记忆网络(LSTM)和双向长短时记忆网络(Bi-LSTM)的电离层TEC单站预测模型相比,本文预测模型的均方根误差(RMSE)平均为原来的80.8%.   相似文献   

3.
2017年9月8日发生了一次强磁暴,Kp指数最大值达到8.利用区域电离层格网模型(Regional Ionosphere Map,RIM)和区域ROTI(Rate of TEC Index)地图,分析了磁暴期间中国及其周边地区电离层TEC扰动特征和低纬地区电离层不规则体的产生与发展情况,同时利用不同纬度IGS(International GNSS Service)测站BJFS(39.6°N,115.9°E),JFNG(30.5°N,114.5°E)和HKWS(22.4°N,114.3°E)的GPS双频观测值,获取各测站的ROTI和DROT(Standard Deviation of Differential ROT)指数变化趋势.结果表明:此次磁暴发生期间电离层扰动先以正相扰动为主,主要发生在中低纬区域,dTEC(differential TEC)最大值达到14.9TECU,随后电离层正相扰动逐渐衰减,在低纬区域发生电离层负相扰动,dTEC最小值达到-7.2TECU;在12:30UT-13:30UT时段,中国南部低纬地区发生明显的电离层不规则体事件;相比BJFS和JFNG两个测站,位于低纬的HKWS测站的ROTI和DROT指数变化更为剧烈,这表明电离层不规则体结构存在纬度差异.   相似文献   

4.
基于加拿大地区高纬度电离层观测网的电离层闪烁观测数据,分析了2018年8月26日地磁暴事件引发的北半球高纬度地区电离层总电子含量(TEC)异常变化、TEC变化率指数(ROTI)及电离层相位闪烁的变化特征.结果表明:加拿大地区最大异常值约6 TECU,磁暴引发全球电离层TEC异常峰值高达20 TECU;加拿大地区电离层相位闪烁发生率最大增至12.6%,而磁静日期间约为1%;强电离层闪烁期间,电离层相位闪烁指数与ROTI之间具有较强的一致性.对GPS双频精密单点定位(Precise Point Positioning,PPP)结果进行分析发现:无闪烁期间定位误差随测站纬度的增高呈现出增大趋势,但均方根误差小于0.4m;闪烁发生期间各测站的定位误差均显著增大,水平和垂直方向定位误差分别增至约0.9m及1.7m.   相似文献   

5.
利用行星际监测数据进行地磁暴预报   总被引:2,自引:0,他引:2  
利用全连接神经网络方法应用于地磁Dst指数的预报中.对ACE卫星探测的太阳风和行星际磁场及其变化对未来几小时的Dst指数的影响进行了统计分析,发现在这些行星际实测参数中,对Dst指数作用较为明显的是太阳风速度、太阳风质子密度和行星际磁场南向分量,同时,当前Dst指数实测值对今后几小时的Dst指数已有很强的制约作用.在统计分析的基础上,建立了全连接神经网络预报模型.由于采用了全连接神经网络结构,模式能够反映出太阳风、行星际磁场等参数与地磁Dst指数参数的复杂联系,可以自动建立输入参量的最佳组合方式,提高了预报精度.通过利用大量实测数据对神经网络模式进行训练,最终建立了利用优选的ACE卫星行星际监测数据提前2 h对Dst指数进行预报.通过检测,预报的误差为14.3%.   相似文献   

6.
近年来,神经网络(Neural Network,简称NN)在非线性系统的预测方面取得了广泛的应用。考虑到卫星钟差包含了复杂的非线性因素,所以将一种新型神经网络-广义回归神经网络(Generalized Regression Neural Network,GRNN)应用于钟差预报中。采用“滑动窗”方式构建样本数据以提高数据利用率,为提高网络的泛化能力,利用K重交叉验证法(K-fold Cross-Validation)对网络进行训练学习,并根据最小均方根误差(Root Mean Square Error,RMSE)确定最优平滑因子。利用国际GNSS服务(International GNSS Service,IGS)公布的精密GPS卫星钟差数据进行预报实验,并与传统二次多项式模型对比分析。结果表明:GRNN模型在24h的预报跨度内的误差可达ns级,并较多项式模型有更好的稳定性;对于线性钟差,GRNN模型要逊于多项式模型,而对于非线性钟差,GRNN模型则明显优于多项式模型,初步验证了GRNN用于钟差预报的可行性、有效性以及实用性。  相似文献   

7.
利用人工神经网络提前1h预报电离层TEC   总被引:1,自引:1,他引:0  
提出了一种利用人工神经网络提前1h预报电离层TEC的简便方法. 考虑到实际工程应用要求, 没有使用其他空间天气参数, 而是选择电离层TEC观测数据本身作为输入参数. 输入参数为当前时刻TEC、一阶差分、相对差分和时间, 输出参数为预报时刻TEC. 利用文中介绍的GPS/TEC处理方法解算厦门站2004年电离层TEC观测数据, 对预报方法进行评估, 全年平均相对误差为9.3744%, 预报结果与观测值相关性达到了0.96678. 结果表明, 利用人工神经网络方法提前1h预报电离层TEC有很好的应用前景.   相似文献   

8.
由IGS工作组提供的全球电离层地图(GIM)是电离层重要的应用数据.卫星高度计能够提供全球实时的电离层延迟误差校正.利用GIM数据,以Jason-3时空分辨率进行电离层总电子含量(TEC)的时间维度插值和空间维度插值,其中空间维度插值采用了Kriging插值和双线性插值两种方法.针对两种插值方法得到的总电子含量,与平滑处理的Jason-3高度计cycle80双频延迟校正值转化的总电子含量进行对比分析.结果显示:其与Kriging插值的平均偏差为0.94TECU,均方根误差为2.73TECU,相关系数为0.91;与双线性插值的平均偏差为1.43TECU,均方根误差为6.85TECU,相关系数为0.61.这说明Kriging插值方法的精度明显高于双线性插值方法.   相似文献   

9.
电离层暴时经验模型STORM在中国区域的适应性研究   总被引:1,自引:1,他引:0       下载免费PDF全文
利用中国区域内9个垂测站1976---1987年一个太阳活动周期的电离层暴时f0F2数据, 统计分析了电离层暴事件的等级, 以及不同等级的电离层暴随季节和地磁纬度的分布特征. 研究发现, 中小型电离层暴在春秋季发生的概率较大, 不同季节的发生次数与地磁纬度具有明显的关系. 利用STORM模型对电离层暴时f0F2和大型及特大型电离层暴时f0F2的预测值与月中值进行了比较. 结果表明, 除了冬季误差增大外, 发生电离层暴时STORM模型能够有效地改善月中值模型. 增加中国的暴时数据, 并提高对冬季的暴时参数f0F2的预测是改善STORM模型的重要因素. 建立合适的暴时指数来预测f0F2是未来研究的重点.   相似文献   

10.
为研究中国陆态网区域电离层TEC在空间小尺度、高分辨率情况下的变化特性及适用精度范围,利用陆态网260个GNSS连续运行观测站数据,解算并生成2016-2017年731天陆态网区域电离层RIM格网,并进行精度验证.在同一RIM格网中,分别在经度和纬度方向上对间隔不同经纬度的TEC格网点作差分析.结果表明:陆态网区域内经度方向上TEC最大变化率和平均变化率分别为0.30TECU·(°)-1和0.11TECU·(°)-1;经度间隔1°时,TEC差值小于2TECU,且随着经度间隔的增大,其TEC差值也随之增大,并表现出一定的半年和周年变化规律;纬度方向上TEC最大变化率和平均变化率分别为1.7TECU·(°)-1和0.46TECU·(°)-1;陆态网区域内电离层TEC随纬度减小而增大,纬度间隔1°时,99.4%的TEC差值小于4TECU,且随着纬度间隔的增大,其TEC差值也随之增大,并表现出一定的半年和周年变化规律;间隔相同情况下,纬度方向上TEC的变化比经度方向上大.   相似文献   

11.
利用两个中纬度台站GPS观测数据提取的GPS卫星硬件延迟,分析了不同太阳活动情况下估算的硬件延迟稳定性和统计特征,结合同期电离层观测数据,研究了电离层状态对硬件延迟估算结果的影响.研究结果表明,基于太阳活动高年(2001年)GPS观测数据估算的硬件延迟稳定性要低于太阳活动低年GPS观测数据的估算结果,利用2001年GPS数据估算的卫星硬件延迟年标准偏差(RMS)平均值约为1TECU,而2009年GPS数据估算的卫星硬件延迟年标准偏差平均值约为0.8TECU.通过对2001年和2009年北京地区电离层F2层最大电子密度(NmF2)变化性分析,结合GPS硬件延迟估算方法对电离层时空变化条件的要求,认为硬件延迟稳定性与太阳活动强度的联系是由不同太阳活动条件下电离层变化的强度差异引起的.   相似文献   

12.
From September 7 to 8, 2017, a G4-level strong geomagnetic storm occurred, which seriously impacted on the Earth’s ionosphere. In this work, the global ionospheric maps released by Chinese Academy of Sciences are used to investigate the ionospheric responses over China and its adjacent regions during the strong storm. The prominent TEC enhancements, which mainly associated with the neutral wind and eastward prompt penetration electric field, are observed at equatorial ionization anomaly crests during the main phase of the storm on 8 September 2017. Compared with those on 8 September, the TEC enhancements move to lower-latitude regions during the recovery phase on 9 September. A moderate storm occurred well before the start of the strong storm causes similar middle-latitude TEC enhancements on 7 September. However, the weak TEC depletion is observed at middle and low latitude on 9–10 September, which could be associated with the prevailing westward disturbance electric field or storm-time neural composition changes. In addition, the storm-time RMS and STD values of the ionospheric TEC grids over China increase significantly due to the major geomagnetic storm. The maximum of the RMS reaches 12.0 TECU, while the maximum of the STD reaches 8.3 TECU at ~04UT on 8 September.  相似文献   

13.
Radial basis function (RBF) interpolation with multi-quadric is developed to perform ionospheric total electron content (TEC) mapping for the Chinese region between 15°N ~ 40°N and 100°E ~ 125°E. TEC measurements from the Centre for Orbit Determination in Europe (CODE) covering the solar maximum year 2011 are used to investigate the performance of the proposed RBF interpolation method. The differences between the RBF interpolated TEC and the CODE TEC are within 0.5 TECU and the root mean square error (RMSE) is very small when 49 data points are used. The maximum difference is ~5 TECU and the error is less than 1 TECU with 25 samples. Our study suggests that a random distribution of measurement points gives smaller RMSEs than a homogenous distribution when the number of sample points is low. The study indicates that RBF interpolation offers a powerful and reliable tool for ionospheric TEC mapping.  相似文献   

14.
The Earth's ionosphere and especially its equatorial part is a highly dynamical medium. Geostationary satellites are known to be a powerful tool for ionospheric studies. Recent developments in BDS-GEO satellites allow such studies on the new level due to the best noise pattern in TEC estimations, which corresponds to those of GPS/GLONASS systems. Here we used BDS-GEO satellites to demonstrate their capability for studying equatorial ionosphere variability on different time scales. Analyzing data from the equatorial SIN1 IGS station we present seasonal variations in geostationary slant TEC for the periods of high (October 2013 - October 2014) and low (January 2017 - January 2018) solar activity, which show semi-annual periodicity with amplitudes about 10 TECU during solar maximum and about 5 TECU during the solar minimum. The 27-day variations are also prominent in geostationary slant TEC variations, which correlates quite well with the variations in solar extreme UV radiation. We found semi-annual pattern in small scale ionospheric disturbances evaluated based on geostationary ROTI index: maximal values correspond to spring and fall equinoxes and minimum values correspond to summer and winter solstices. The seasonal asymmetry in ROTI values was observed: spring equinox values were almost twice as higher than fall equinox ones. We also present results on the 2017 May 28–29 G3 geomagnetic storm, when ~30 TECU positive anomaly was recorded, minor and final major sudden stratospheric warmings in February and March 2016, with positive daytime TEC anomalies up to 15–20 TECU, as well as the 2017 September 6 X9.3 solar flare with 2 TECU/min TEC rate. Our results show the large potential of geostationary TEC estimations with BDS-GEO signals for continuous monitoring of space weather effects in low-latitude and equatorial ionosphere.  相似文献   

15.
In this research, as part of working towards improving the IRI over equatorial region, the total electron content (TEC) derived from GPS measurements and IRI-2007 TEC predictions at Chumphon station (10.72°N, 99.37°E), Thailand, during 2004–2006 is analyzed. The seasonal variation of the IRI-2007 TEC predictions is compared with the TEC from the IRI-2007 TEC model with the option of the actual F2 plasma frequency (foF2) measurements as well as the TEC from the GPS and International GNSS service (IGS). The Chumphon station is located at the equatorial region and the low latitude of 3.22°N. For a declining phase of the solar cycle (2004–2006), the study shows that the IRI-2007 TEC underestimates the IRI-2007 TEC with the foF2 observation at the nighttime by about 5 TECU. The maximum differences are about 15 TECU during daytime and 5 TECU during nighttime. The overestimation is more evident at daytime than at nighttime. When compared in terms of the root-mean square error (RMSE), we find that the highest RMSE between GPS TEC and IRI 2007 TEC is 14.840 TECU at 1230 LT in 2004 and the lowest average between them is 1.318 TECU at 0630 LT in 2006. The noon bite-out phenomena are clearly seen in the IRI-2007 TEC with and without optional foF2 measurements, but not on the GPS TEC and IGS TEC. The IRI TEC with optional foF2 measurements gives the lowest RMSE values between IRI TEC predicted and TEC measurement. However, the TEC measurements (GPS TEC and IGS TEC) are more correct to use at Chumphon station.  相似文献   

16.
Moderate geomagnetic storms occurred during January 22–25, 2012 period. The geomagnetic storms are characterized by different indices and parameters. The SYM-H value on January 22 increased abruptly to 67 nT at sudden storm commencement (SSC), followed by a sharp decrease to −87 nT. A second SSC on January 24 followed by a shock on January 25 was also observed. These SSCs before the main storms and the short recovery periods imply the geomagnetic storms are CME  -driven. The sudden jump of solar wind dynamic pressure and IMF BzBz are also consistent with occurrence of CMEs. This is also reflected in the change in total electron content (TEC) during the storm relative to quiet days globally. The response of the ionospheric to geomagnetic storms can also be detected from wave components that account for the majority of TEC variance during the period. The dominant coherent modes of TEC variability are diurnal and semidiurnal signals which account upto 83% and 30% of the total TEC variance over fairly exclusive ionospheric regions respectively. Comparison of TEC anomalies attributed to diurnal (DW1) and semidiurnal (SW2) tides, as well as stationary planetary waves (SPW1) at 12 UTC shows enhancement in the positive anomalies following the storm. Moreover, the impact of the geomagnetic storms are distinctly marked in the daily time series of amplitudes of DW1, SW2 and SPW1. The abrupt changes in amplitudes of DW1 (5 TECU) and SW2 (2 TECU) are observed within 20°S–20°N latitude band and along 20°N respectively while that of SPW1 is about 3 TECU. Coherent oscillation with a period of 2.4 days between interplanetary magnetic field and TEC was detected during the storm. This oscillation is also detected in the amplitudes of DW1 over EIA regions in both hemispheres. Eventhough upward coupling of quasi two day wave (QTDWs) of the same periodicity, known to have caused such oscillation, are detected in both ionosphere and upper stratosphere, this one can likely be attributed to the geomagnetic storm as it happens after the storm commencement. Moreover, further analysis has indicated that QTDWs in the ionosphere are strengthened as a result of coherent oscillation of interplanetary magnetic field with the same frequency as QTDWs. On the otherhand, occurrences of minor SSW and geomagnetic storms in quick succession complicated clear demarcation of attribution of the respective events to variability of QTDWs amplitudes over upper stratosphere.  相似文献   

17.
地磁暴是空间天气预报的重要对象.在太阳活动周下降年和低年,冕洞发出的高速流经过三天左右行星际传输到达地球并引发的地磁暴占主导地位.目前地磁暴的预报通常依赖于1AU处卫星就位监测的太阳风参数,预报提前量只有1h左右.为了增加地磁暴预报提前量,需要从高速流和地磁暴的源头即太阳出发,建立冕洞特征参数与地磁暴的定量关系.分析了2010年5月到2016年12月的152个冕洞-地磁暴事件,利用SDO/AIA太阳极紫外图像提取了两类冕洞特征参数,分析了其与地磁暴期间ap,Dst和AE三种地磁指数的统计关系,给出冕洞特征参数与地磁暴强度以及发生时间的统计特征,为基于冕洞成像观测提前1~3天预报地磁暴提供了依据.   相似文献   

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